It detects minute changes in electrical signals to perform diagnostic tests such as facility diagnosis, safety diagnosis, welding diagnosis, and secondary battery diagnosis. It also attaches an IoT sensor to facilities, buildings, and devices to monitor transient phenomena such as device over-current and over-vibration in real time. It can use big data to expand its scope of coverage to IoT-based process management and energy management.
|Input||Power||DC 12 ~ 32V|
|Specification||Signal processing||DSP / FPGA(8ns)
– Transmission of 1 frame (8KB) per 50 msec (reception criteria)
DIO : Isolation Input/Output X 4(5V ~ 24V)
|Function||Independent trigger feature by channel
Screen Zoom feature (X: 10 DIV, Y: 10 DIV)
Application of smart factory, facilities and precision measurement of equipment
ㆍIt is equipped with a simple scope that provides a multi-channel independent trigger function and a firmware that can collect signal data.
ㆍIt provides the Trigger Mode Signal Logger and Demo Library, so that a predictive maintenance system based on the original signal high-speed processing of big data and edge computing, which is a major issue in the smart factory industry, can be built reasonably and economically.
ㆍProvide compatibility of various interfaces suitable for high-speed signal processing environment in IoT-related business fields such as Smart Factory/Building/City
ㆍProvide a system linking with government agencies, large corporations and SI companies in connection with IoT business
ㆍProvide resources for diagnostic equipment, telecommunication service providers, SI solutions and big data companies
ㆍEasy in edge computing of big data such as IoT-based factories/construction/farms
ㆍPossible to introduce Smart – System at a low price – Increase productivity and recruit manpower for new business sectors
ㆍModule unit and systemization are expected to contribute to overseas exports – Domestic development and stabilization are expected to contribute to overseas promotion and export
ㆍProduction cost reduction effect – If deep learning analysis is provided to big data, predictive maintenance can be made possible through normal operation of facilities, deterioration progress, and trend monitoring, leading to maximization of opportunity costs
Signal Logger TCP/IP & Measuring Setup
Signal Logger Data Base Monitor
Running Status & Alarm Monitor